{"id":"W2101956459","doi":"10.1145/2557642.2563678","title":"YawDD","year":2014,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":270,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Dash; Video camera; Benchmark (surveying); Front (military); Computer graphics (images); Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004221458,0.001471061,0.0007621861,0.001106012,0.0005282455,0.001554303,0.0009729892,0.0008072281,0.0512127],"category_scores_gemma":[0.001373513,0.0003990866,0.000746646,0.0007294929,0.0002253972,0.0016111,0.001166842,0.0006569956,0.03538397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003545545,"about_ca_system_score_gemma":0.0003649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003465651,"about_ca_topic_score_gemma":0.004048241,"domain_scores_codex":[0.9994019,0.0000457514,0.00003823665,0.0002940833,0.0001442041,0.00007578066],"domain_scores_gemma":[0.9995993,0.00005080051,0.00003986853,0.0001290779,0.0001547883,0.00002613595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001155424,0.0001564815,0.01540142,0.001120977,0.0001730079,0.0006641576,0.0002713556,0.01348782,0.02658255,0.01041084,0.197477,0.733099],"study_design_scores_gemma":[0.0001472018,0.0004530071,0.02565232,0.000313113,0.000165139,0.002386705,0.0005891986,0.1206756,0.04945849,0.01202593,0.7879431,0.0001902195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09121922,0.008024365,0.5467531,0.001098051,0.005011889,0.0009661078,0.09402981,0.05632823,0.1965693],"genre_scores_gemma":[0.4198311,0.004853376,0.1852868,0.001720719,0.0008023914,0.0007416168,0.215341,0.004658523,0.1667644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0512127,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198600600739313,"score_gpt":0.2561424033236177,"score_spread":0.2441563973162246,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}